Jigsaw rule-based data verification method, apparatus and device, medium and product

Abstract

The invention discloses a data verification method and device based on a puzzle rule, equipment, a medium and a product. The method comprises the following steps: acquiring historical flight data within a certain time; wherein the historical flight data at least comprises leg data, flow direction data and fuel quantity data; performing abnormal data verification on the historical flight data by adopting a preset puzzle rule to obtain abnormal flight data conforming to the preset puzzle rule; wherein the preset jigsaw rules at least comprise a leg jigsaw rule, a flow direction jigsaw rule and an oil mass jigsaw rule; and if the abnormal flight data conforming to the preset puzzle rule does not exist, checking the preset puzzle rule to update the preset puzzle rule. According to the method, abnormal data verification can be automatically carried out on flight segments, flow directions and fuel quantities input every month according to the pre-defined and packaged puzzle rules, so that the efficiency and accuracy of flight abnormal data verification are improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of aviation data, and in particular to a data checking method and device based on a jigsaw rule, equipment, medium and product. BACKGROUND

[0002] Due to the rapid development of China's civil aviation transportation industry, the civil aviation flight business volume has greatly increased, and airlines need to regularly report relevant flight information data to the Civil Aviation Administration every month to assist the Civil Aviation Administration in clarifying the industry operation, and researching and adjusting the optimization of civil aviation business direction. Therefore, before the flight data is sorted, classified and output into a report, it needs to be checked multiple times through multiple rules, and the abnormal flight data screened out needs to be corrected before being used to generate a monthly flight data report, so as to ensure the accuracy of the flight data reported to the Civil Aviation Administration every month.

[0003] At present, in the flight data processing, the aviation production statistics system can integrate flight production and transportation data reception, data import, data generation and report output into one, and a very mature system mechanism has been formed from data acquisition to report generation. However, in the flight abnormality data checking, such as flight segment abnormality checking, the flight data entry is mainly checked manually in a single review manner, and the problematic flight data is corrected by manual screening. Such a method needs to consume a large amount of human time cost, has serious lag, and cannot avoid human errors / mistakes, omissions and other drawbacks, and it is difficult to ensure the efficiency and accuracy of flight data statistics. SUMMARY

[0004] The present application provides a data checking method and device based on a jigsaw rule, equipment, medium and product, which checks the abnormality of flight data by pre-defining a packaged jigsaw rule, so as to improve the efficiency and accuracy of flight abnormality data checking, and thus improve the efficiency and accuracy of flight data statistics.

[0005] In order to achieve the above-mentioned purpose, the embodiment of the present application provides a data checking method based on a jigsaw rule, comprising:

[0006] acquiring historical flight data of a certain time; wherein the historical flight data at least includes flight segment data, flow direction data and oil quantity data;

[0007] checking the abnormality of the historical flight data by using a preset jigsaw rule to obtain abnormal flight data conforming to the preset jigsaw rule; wherein the preset jigsaw rule at least includes a flight segment jigsaw rule, a flow direction jigsaw rule and an oil quantity jigsaw rule;

[0008] if there is no abnormal flight data conforming to the preset jigsaw rule, checking the preset jigsaw rule to update the preset jigsaw rule.

[0009] As an improvement of the above scheme, the preset puzzle rule is used to check the abnormality of the historical flight data, and abnormal flight data conforming to the preset puzzle rule is obtained, including:

[0010] The preset puzzle rule is parsed to generate a rule formula of the preset puzzle rule;

[0011] According to the table field of the rule formula, the historical flight data is retrieved to obtain historical flight data corresponding to the table field;

[0012] The value of the corresponding historical flight data is substituted into the rule formula to obtain abnormal flight data conforming to the preset puzzle rule.

[0013] As an improvement of the above scheme, the generation method of the preset puzzle rule includes:

[0014] The rule value range and rule condition of the preset puzzle rule are set by using a puzzle rule tool, and the set rule value range and rule condition are assembled to obtain the corresponding preset puzzle rule.

[0015] As an improvement of the above scheme, the puzzle rule tool includes a reference table, a comparison table, a tool block, a variable block, a puzzle board, and a function area;

[0016] The reference table and the comparison table are used to provide a table field conforming to the rule value range;

[0017] The tool block is used to splice the table field and mark the annotation to obtain a rule value puzzle of the table field, and the rule value puzzle is combined and operated to obtain a rule condition puzzle of the rule value puzzle;

[0018] The variable block is used to store the rule value puzzle;

[0019] The puzzle board is used to assemble the rule value puzzle and the rule condition puzzle to obtain the corresponding preset puzzle rule;

[0020] The function area is used to save the corresponding preset puzzle rule and view the description of the corresponding preset puzzle rule.

[0021] As an improvement of the above scheme, if there is no abnormal flight data conforming to the preset puzzle rule, the preset puzzle rule is checked to update the preset puzzle rule, including:

[0022] If there is no abnormal flight segment data conforming to the flight segment puzzle rule, the flight segment puzzle rule is checked to update the flight segment puzzle rule;

[0023] If there is no abnormal flow data meeting the flow direction puzzle rule, the flow direction puzzle rule is checked to update the flow direction puzzle rule.

[0024] If there is no abnormal oil quantity data meeting the oil quantity puzzle rule, the oil quantity puzzle rule is checked to update the oil quantity puzzle rule.

[0025] As an improvement of the above scheme, the flight segment puzzle rule is used to check whether there is abnormal flight segment data in the historical flight data.

[0026] The flow direction puzzle rule is used to check whether there is abnormal flow direction data in the historical flight data.

[0027] The oil quantity puzzle rule is used to check whether there is abnormal oil quantity data in the historical flight data.

[0028] To achieve the above object, the embodiment of the present application provides a data checking device based on a puzzle rule, comprising:

[0029] A flight data acquisition module is configured to acquire historical flight data in a certain time period, wherein the historical flight data at least includes flight segment data, flow direction data and oil quantity data.

[0030] An abnormal data checking module is configured to perform abnormality data checking on the historical flight data by using a preset puzzle rule to obtain abnormal flight data meeting the preset puzzle rule, wherein the preset puzzle rule at least includes a flight segment puzzle rule, a flow direction puzzle rule and an oil quantity puzzle rule.

[0031] A puzzle rule updating module is configured to check the preset puzzle rule to update the preset puzzle rule if there is no abnormal flight data meeting the preset puzzle rule.

[0032] To achieve the above object, the embodiment of the present application correspondingly provides a data checking device based on a puzzle rule, comprising a processor, a memory and a computer program stored in the memory and configured to be executed by the processor, wherein the processor executes the computer program to implement the above data checking method based on a puzzle rule.

[0033] To achieve the above object, the embodiment of the present application further provides a computer readable storage medium, which comprises a stored computer program, wherein the computer program controls the device where the computer readable storage medium is located to execute the above data checking method based on a puzzle rule when the computer program is running.

[0034] To achieve the above object, the embodiment of the present application further provides a computer program product stored in a storage medium, wherein the program product is executed by at least one processor to implement the steps of the data verification method based on the puzzle rule.

[0035] Compared with the prior art, the data verification method, device, equipment, medium and product based on the puzzle rule disclosed by the embodiment of the present application can obtain historical flight data in a certain time period, wherein the historical flight data at least includes flight segment data, flow direction data and oil quantity data; the historical flight data is subjected to abnormality data verification by using a preset puzzle rule to obtain abnormal flight data conforming to the preset puzzle rule; wherein the preset puzzle rule at least includes a flight segment puzzle rule, a flow direction puzzle rule and an oil quantity puzzle rule; if there is no abnormal flight data conforming to the preset puzzle rule, the preset puzzle rule is checked to update the preset puzzle rule. The abnormality data verification of the flight data according to the puzzle rule defined in advance can reduce the labor time cost, avoid the drawbacks of human errors / omissions and the like, improve the efficiency and accuracy of the abnormality data verification of the flight data, and thus improve the efficiency and accuracy of the flight data statistics. BRIEF DESCRIPTION OF DRAWINGS

[0036] Figure 1 is a flow diagram of the data verification method based on the puzzle rule provided by the embodiment of the present application;

[0037] Figure 2 is a structural diagram of the data verification device based on the puzzle rule provided by the embodiment of the present application;

[0038] Figure 3 is a structural block diagram of the data verification equipment based on the puzzle rule provided by the embodiment of the present application. DETAILED DESCRIPTION

[0039] The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, but not all the embodiments of the present application. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor fall within the scope of protection of the present application.

[0040] It should be noted that the terms "include" and "specifically" and any variations thereof in the present application are intended to cover non-exclusive inclusion, for example, a process, method, system, product or device including a series of steps or units does not have to be limited to the clearly listed steps or units, but can include other steps or units that are not clearly listed or inherent to the process, method, product or device.

[0041] Referring to Figure 1 , Figure 1 is a flowchart of a data checking method based on a puzzle rule provided by an embodiment of the present application. The data checking method based on the puzzle rule comprises:

[0042] S1, obtaining historical flight data in a certain time period; wherein the historical flight data at least comprises segment data, flow direction data and fuel quantity data;

[0043] S2, performing abnormality data checking on the historical flight data by using a preset puzzle rule to obtain abnormal flight data conforming to the preset puzzle rule; wherein the preset puzzle rule at least comprises segment puzzle rule, flow direction puzzle rule and fuel quantity puzzle rule;

[0044] S3, if there is no abnormal flight data conforming to the preset puzzle rule, checking the preset puzzle rule to update the preset puzzle rule.

[0045] Exemplarily, the data checking method based on the puzzle rule provided by the embodiment of the present application can be implemented by a data checking server. The data checking server can be carried in an aviation production statistical system or exist independently of the aviation production statistical system. The data checking server can interact with a user and the aviation production statistical system. The data checking server obtains historical flight data (such as transportation entry production data in the aviation production statistical system, including segment data, flow direction data, fuel quantity data, route data, crew data, etc.) in a certain time period (such as every month, every year, etc.) from the aviation production statistical system. The data checking server performs abnormality data checking on the historical flight data by using a preset puzzle rule (the preset puzzle rule is defined in advance by a puzzle rule tool) to obtain flight data within the range of the preset puzzle rule. The flight data is abnormal flight data (such as abnormal segment data, abnormal flow direction data and abnormal fuel quantity data). If there is no flight data within the range of the preset puzzle rule, a detection abnormality prompt is output. The preset puzzle rule is checked to update the preset puzzle rule. The updated preset puzzle rule is used in subsequent abnormality data checking. The detection abnormality prompt is that the value of the flight data does not exist in the aviation production statistical system. It is suggested to check whether the value in the preset puzzle rule is correct. The flight data can be checked for abnormality according to the pre-defined and encapsulated puzzle rule. The human time cost is reduced. The disadvantages such as human error, omission, etc. are avoided. The efficiency and accuracy of flight abnormality data checking are improved. The efficiency and accuracy of flight data statistics are improved.

[0046] Specifically, the step S2 comprises:

[0047] S21, parse the preset jigsaw puzzle rules to generate the rule formula of the preset jigsaw puzzle rules;

[0048] S22, according to the table fields of the rule formula, perform data retrieval on the historical flight data to obtain the historical flight data corresponding to the table fields;

[0049] S23, substitute the corresponding historical flight data values ​​into the rule formula to obtain abnormal flight data that conforms to the preset puzzle rule.

[0050] For example, the data verification server can parse a preset jigsaw puzzle rule (the preset jigsaw puzzle rule format is image XML) through a content program to generate a rule formula for the preset jigsaw puzzle rule, and send the rule formula to the aviation production statistics system. The aviation production statistics system uses a constraint program to retrieve the table fields involved in the rule formula. If the aviation production statistics system can find the corresponding table field, it obtains the actual value of the corresponding table field in the historical flight data, and sends the actual value of the corresponding table field to the content program of the data verification server one by one. All the actual values ​​of the corresponding table fields are then substituted into the rule formula to obtain abnormal flight data that conforms to the preset jigsaw puzzle rule, and the abnormal flight data is displayed on the corresponding interface. This embodiment of the invention can quickly obtain abnormal flight fuel volume, flow direction, and flight segment data within the scope of various verification rules. Compared with the previous manual single-line review and screening method, it saves manpower and time costs to the greatest extent, improves work efficiency, and reduces the error rate that may be caused by manual screening by using the aviation production statistics system for screening.

[0051] In a specific implementation, when the segment mosaic rule stipulates that the absolute value of the difference between air time and FIC air time is greater than or equal to a fixed percentage of FIC air time, the aviation production statistics system verifies each value in the segment mosaic rule, checking if both air time and FIC air time exist in the system. If they do, all values ​​are substituted into the formula of the segment mosaic rule and executed, thereby displaying the abnormal segment data within the specified range on the corresponding interface. It is worth noting that the fixed percentage of FIC air time can be set using expert experience, such as 50%.

[0052] In a specific embodiment, when the flow direction puzzle rule is Adult + Child ≠ 0 and Baggage = 0, the aviation production statistics system verifies each value of the rule of the flow direction puzzle rule, checks whether there are adults, children, and baggage in the aviation production statistics system, and if there are, substitutes all values ​​into the formula of the flow direction puzzle rule and runs it, thereby displaying abnormal flow direction data within the range of conditions on the corresponding interface.

[0053] In a specific embodiment, when the fuel quantity mosaic rule is that the absolute value of the fuel quantity at the ACARS docking time in the original fuel stock + new refueling - FIC is greater than or equal to a fixed value, the aviation production statistics system verifies each value of the fuel quantity mosaic rule. It checks whether there are new refueling, original fuel stock, or docking time fuel quantities in the aviation production statistics system. If so, all values ​​are substituted into the formula of the fuel quantity mosaic rule and the process is executed, thereby displaying abnormal fuel quantity data within the specified range on the corresponding interface. It is worth noting that the fixed value can be set as needed.

[0054] Furthermore, the method for generating the preset puzzle rules includes:

[0055] The jigsaw puzzle rule tool is used to set the rule value range and rule conditions of the preset jigsaw puzzle rule, and the set rule value range and rule conditions are assembled to obtain the corresponding preset jigsaw puzzle rule.

[0056] The jigsaw puzzle rule tool described in this embodiment of the invention can maximize the satisfaction of data statisticians when screening abnormal data in various scenarios such as flight segments, flow directions, and fuel quantities. It allows them to set various verification rules at any time without having to write code. Compared with the previous code implementation method, the operation is simpler, the threshold for use is lower, and it is applicable to a wider range of people.

[0057] For example, the flight segment mosaic rule is mainly used to verify whether the error between the air time of the entered flight segment data and the air time of the FIC (FICFlight Information Center) exceeds the standard range (e.g., the absolute value of the difference between air time and FIC air time ≥ a fixed percentage of FIC air time); the rule value setting of the flight segment mosaic rule (e.g., table fields for specific values ​​of air time and FIC air time, and linking the two table fields through specific flight information (e.g., flight number, flight date, flight time); the rule condition setting of the flight segment mosaic rule (e.g., the absolute value of the difference between air time and FIC air time ≥ a fixed percentage of FIC air time); the flight segment mosaic rule is obtained by splicing the rule value mosaic and the rule condition mosaic, and then the flight segment mosaic rule is saved.

[0058] The flow direction puzzle rule is mainly used to verify whether there are any input anomalies in flow direction data (such as adult, child, infant, cargo, mail, and baggage data). Adult, child, infant, cargo, mail, and baggage data all need to be taken from the actual flight segment table fields. When the rule is "Adult + Child ≠ 0, Baggage = 0", the flow direction puzzle rule needs to piece together two parts of the puzzle content: one part is the rule value, that is, the values ​​of adult, child, and baggage are taken to the specific table fields, and the various fields are linked to the table through specific flight information. The other part is the rule condition setting, such as "Empty Adult + Child ≠ 0, Baggage = 0". The flow direction puzzle rule is obtained by piecing together the puzzle content (rule value puzzle and rule condition puzzle) and then saved.

[0059] Fuel quantity mosaic rules are primarily used to verify whether fuel quantity data (such as original fuel, new refueling, retained fuel, fuel consumption, etc.) has been entered abnormally. Specifically, based on the data entered during flight data entry for new refueling, retained fuel, original fuel, and fuel consumption, the corresponding values ​​of the FIC dynamic time and the fuel quantity table data for the time-of-arrival fuel and the fuel quantity at the stop time are derived. When the rule is that the absolute value of the fuel quantity at the stop time in the FIC (Aircraft Communications Addressing and Reporting System) of original fuel + new refueling ≥ a fixed value, the fuel quantity mosaic rule needs to complete two parts of the mosaic: one part is the rule value retrieval, such as retrieving the values ​​of new refueling, original fuel, and fuel quantity at the stop time to specific table fields, and linking these fields to the table using specific flight information; the other part is the setting of the rule conditions, such as the absolute value of the fuel quantity at the stop time in the FIC (Aircraft Communications Addressing and Reporting System) of original fuel + new refueling ≥ a fixed value. The oil quantity puzzle rule is obtained by piecing together the puzzle contents (rule value puzzle and rule condition puzzle) of the oil quantity puzzle rule, and then the oil quantity puzzle rule is saved.

[0060] Specifically, the jigsaw puzzle rule tool includes a baseline table, a reference table, tool blocks, variable blocks, a puzzle board, and a function area;

[0061] The benchmark table and the comparison table are used to provide table fields that conform to the value range of the rules;

[0062] The tool block is used to concatenate the table fields and add annotations to obtain the rule value puzzle of the table fields, and to perform combination operations on the rule value puzzle to obtain the rule condition puzzle of the rule value puzzle;

[0063] The variable block is used to store the rule value puzzle;

[0064] The puzzle board is used to assemble the rule value puzzle and the rule condition puzzle to obtain the corresponding preset puzzle rule;

[0065] The function area is used to save the corresponding preset puzzle rules and view the description of the corresponding preset puzzle rules.

[0066] For example, the baseline table mainly refers to the transportation entry production data table in the aviation production statistics system. This production data table includes route data tables, flight segment data tables, flow direction data tables, fuel quantity data tables, and crew data tables. The baseline table primarily provides table fields that conform to the stated rule value range and rule conditions (e.g., the value fields of flight data that meet the condition range for location setting rules). The lookup table is a supplementary data table associated with the baseline table. It's understood that because the baseline table has limited fields, it's impossible to locate all flight data fields using the baseline table alone. Therefore, the lookup table serves as a supplement. When it's necessary to locate a flight data field in the baseline table using a field from the lookup table, the field can be located by associating it with the baseline table fields. It's worth noting that the data range of the lookup table can be all other data tables in the aviation production statistics system that are related to the baseline table. The lookup table serves the same purpose as the baseline table, primarily providing table fields that conform to the stated rule value range and rule conditions; such as the value fields for location setting rules.

[0067] Tool blocks: The settings of the baseline table, reference table and related rule conditions (corresponding table fields) are all linked through tool blocks before they can be merged into a whole rule for calculation. The main puzzle blocks contained in the tool blocks are: (1) Tool blocks applied to declaring variable values ​​include variable declaration blocks, comments, calculation results, association tables and variable operator blocks. Tool blocks for declaring variable values ​​are used to perform operations such as value taking, annotation marking and table field association of the table fields of the reference table and the baseline table. It is worth noting that the tool blocks for declaring variable values ​​can be flexibly combined and used according to different preset jigsaw puzzle rules; the variable operator blocks (addition, subtraction, multiplication, division, greater than, less than, equal to, and or...) are operator blocks used to associate the lookup table with the base table; (2) The tool blocks applied to the rule condition setting include the condition setting block and the condition operator block. The tool blocks for setting the rule conditions are used to perform operations such as splicing and calculation on the table fields of the rule conditions of the preset jigsaw puzzle rules; it is worth noting that the condition operator blocks (addition, subtraction, multiplication, division, greater than, less than, equal to, and or...) are input operators used to customize the numerical or textual settings of the rule conditions. The condition setting blocks can be flexibly combined and used according to the rule conditions of different preset jigsaw puzzle rules. It is understandable that each preset jigsaw puzzle rule has its own unique attributes. If the attributes of the tool blocks used conflict with each other, the jigsaw puzzles of the conflicting tool blocks cannot be spliced ​​together. Variable operators used for the association between lookup tables and base tables (e.g., lookup table a equals base table b) can only be used in the tool block of the calculation result and the associated table when used for the associated table. If used in a calculation scenario (e.g., value a equals value b), they will be mutually exclusive and cannot be successfully concatenated.

[0068] Variable Block: The data in the variable block comes from each declared variable (rule value puzzle) of the current preset puzzle rule. When the tool block concatenates and annotates specific fields in the baseline table or reference table (e.g., when declaring a variable value, the air time field in the baseline table-flight segment table is selected, and the declared variable is annotated as air time), the declared variable will be packaged into a whole and displayed in the variable block, showing the annotation name (e.g., air time). Once the user completes the setting of the declared variable (rule value puzzle), they can directly drag and drop this declared variable in the condition operator block in the condition setting block to apply it, obtaining the rule condition puzzle. Its main purpose is to reduce the difficulty of use for users and to make the overall rule setting interface concise, clear, and uncluttered.

[0069] The puzzle area is mainly a canvas area for assembling puzzle pieces, used to assemble the rule value puzzle pieces and the rule condition puzzle pieces to obtain the corresponding preset puzzle rules.

[0070] The function area contains three buttons: Save Rules, Maximize Canvas, and Generate Description. The function area is mainly used to save the corresponding preset jigsaw puzzle rules and view their descriptions. Specifically: the Save Rules button is used to save the jigsaw puzzle rules; the Maximize Canvas button is used to maximize the canvas; and the Generate Description button is used to generate a text description based on the content of the preset jigsaw puzzle rules before saving the rules, allowing users to check whether the generated rules match the intended rules.

[0071] The jigsaw puzzle rule tool used in this embodiment of the invention encapsulates various verification rules. Compared with the previous rule verification method implemented through code, it has the characteristics of visual programming, stronger reusability and extensibility, and does not require code modification and rewriting due to rule changes, which helps to reduce development costs.

[0072] In a specific implementation, a baseline table or lookup table, combined with tool blocks, is used to locate the values ​​of all declared variables within the rule. For example, in the rule: "Airtime - absolute value of FIC airtime ≥ FIC airtime * 50%", the values ​​of airtime and FIC airtime are first located and annotated. After annotating, this declared variable is packaged into a whole and a variable named after the annotation is generated in the variable block. Using conditional operation blocks and operators, the generated variable block is used to set the rule (e.g., "Airtime - absolute value of FIC airtime ≥ FIC airtime * 50%)" and saved. The program sends this successfully saved jigsaw puzzle rule in XML format to the aviation production statistics system to determine if the values ​​involved in the rule (e.g., airtime, FIC airtime) exist in the aviation production statistics system. If all exist, the values ​​can be substituted into the conditional formula for calculation. If one of the values ​​does not exist, the process stops and a message is displayed in the aviation production statistics system: "The corresponding value does not exist in the aviation production statistics system. Please check if the jigsaw puzzle is correct." If the values ​​involved in the rule (such as air time, FIC air time) exist in the aviation production statistics system, then this value field will be substituted into the specific formula for calculation, and the data that meets the conditions will be retrieved in the aviation production statistics system and displayed on the designated interface; if no data that meets the rule is retrieved, then the designated interface will display: No data available.

[0073] Specifically, step S3 includes:

[0074] S31. If there is no abnormal segment data that matches the segment mosaic rules, the segment mosaic rules are checked and updated.

[0075] S32, if there is no abnormal flow data that matches the flow pattern rule, check the flow pattern rule to update the flow pattern rule;

[0076] S33, if there is no abnormal oil volume data that matches the oil volume mosaic rule, check the oil volume mosaic rule to update the oil volume mosaic rule.

[0077] For example, if a value in a segment mosaic rule (e.g., flight time or FIC flight time) does not exist in the aviation production statistics system, the program is stopped and a segment error message is displayed on the corresponding interface. The segment mosaic rule is then checked, and the rule value is modified based on the check results to obtain an updated segment mosaic rule. It is worth noting that the segment error message indicates that a value in the segment mosaic rule does not exist in the aviation production statistics system; please check if the value in the segment mosaic rule is correct. The value selection logic and operational logic of different segment mosaic rules are consistent.

[0078] If a value in the flow direction puzzle rule (e.g., adult, child, or baggage) does not exist in the aviation production statistics system, the program will stop and a flow direction error message will be displayed on the corresponding interface. The flow direction puzzle rule will be checked, and the rule values ​​will be modified according to the check results to obtain an updated flow direction puzzle rule. It is worth noting that the flow direction error message indicates that a value in the flow direction puzzle rule does not exist in the aviation production statistics system; please check whether the value in the flow direction puzzle rule is correct. The value selection logic and operation logic of different flow direction puzzle rules are consistent.

[0079] If a value in the fuel level mosaic rule (e.g., new refueling, existing fuel, or fuel level at the time of docking) does not exist in the aviation production statistics system, the program will stop and display a fuel level anomaly message on the corresponding interface. The fuel level mosaic rule will be checked, and the rule values ​​or conditions will be modified based on the check results to obtain an updated fuel level mosaic rule. It is worth noting that the fuel level anomaly message indicates that a value in the fuel level mosaic rule does not exist in the aviation production statistics system; please check if the value in the fuel level mosaic rule is correct. The value selection logic and operational logic of different fuel level mosaic rules are consistent.

[0080] Specifically, the flight segment mosaic rules are used to check whether there are any anomalies in the flight segment data in the historical flight data;

[0081] The flow direction puzzle rule is used to check whether there are any anomalies in the flow direction data in the historical flight data;

[0082] The fuel quantity mosaic rule is used to check whether there are any anomalies in the fuel quantity data in the historical flight data.

[0083] For example, in this embodiment of the invention, relevant rules for verifying flight segment data, flow data, and fuel volume data can be formulated according to the relevant regulations on business statistics. Taking flight segment data as an example, flight segment data includes the value rules for each time node of the flight and the verification rules between fields. After the rules are generated, data within the verification range that meets the conditions can be obtained through a fixed page.

[0084] The embodiments of the present invention can meet the needs of changing or adding verification rules anytime and anywhere due to changes in the verification scenario caused by changes in business requirements. It can effectively assist business personnel in creating new rules or modifying old rules at any time, so as to obtain abnormal data of flight production and transportation as quickly as possible and improve the efficiency of business data processing.

[0085] This invention discloses a data verification method based on jigsaw puzzle rules. The method involves acquiring historical flight data over a certain period, where the historical flight data includes at least segment data, flow direction data, and fuel quantity data. Anomaly verification is performed on the historical flight data using preset jigsaw puzzle rules to obtain abnormal flight data that conforms to the preset rules. The preset jigsaw puzzle rules include at least segment jigsaw puzzle rules, flow direction jigsaw puzzle rules, and fuel quantity jigsaw puzzle rules. If no abnormal flight data conforms to the preset jigsaw puzzle rules, the preset jigsaw puzzle rules are checked and updated. Performing anomaly verification on flight data based on predefined and encapsulated jigsaw puzzle rules reduces manpower and time costs, avoids human errors / mistakes and omissions, and improves the efficiency and accuracy of flight anomaly verification, thereby improving the efficiency and accuracy of flight data statistics.

[0086] See Figure 2 , Figure 2 This is a schematic diagram of a data verification device 10 based on jigsaw puzzle rules provided in an embodiment of the present invention. The data verification device 10 based on jigsaw puzzle rules includes:

[0087] The flight data acquisition module 11 is used to acquire historical flight data over a certain period of time; wherein, the historical flight data includes at least flight segment data, flow direction data, and fuel volume data;

[0088] The abnormal data verification module 12 is used to perform abnormal data verification on the historical flight data using preset puzzle rules to obtain abnormal flight data that conforms to the preset puzzle rules; wherein, the preset puzzle rules include at least flight segment puzzle rules, flow direction puzzle rules and fuel quantity puzzle rules;

[0089] The puzzle rule update module 13 is used to check the preset puzzle rule and update it if there is no abnormal flight data that matches the preset puzzle rule.

[0090] The data verification device 10 based on jigsaw puzzle rules provided in this embodiment of the invention can realize all the processes of the data verification method based on jigsaw puzzle rules in the above embodiments. The functions and technical effects of each module in the device are the same as the functions and technical effects of the data verification method based on jigsaw puzzle rules in the above embodiments, and will not be repeated here.

[0091] See Figure 3 , Figure 3This is a schematic diagram of the structure of a data verification device 20 based on jigsaw puzzle rules provided in an embodiment of the present invention. The data verification device 20 based on jigsaw puzzle rules in this embodiment includes: a processor 21, a memory 22, and a computer program stored in the memory 22 and executable on the processor 21. When the processor 21 executes the computer program, it implements the steps in the above-described data verification method embodiment based on jigsaw puzzle rules. Alternatively, when the processor 21 executes the computer program, it implements the functions of each module in the above-described data verification device embodiment based on jigsaw puzzle rules.

[0092] For example, the computer program may be divided into one or more modules, which are stored in the memory 22 and executed by the processor 21 to complete the present invention. The one or more modules may be a series of computer program instruction segments capable of performing specific functions, which describe the execution process of the computer program in the data verification device 20 based on jigsaw puzzle rules.

[0093] The data verification device 20 based on jigsaw puzzle rules can be a computing device such as a desktop computer, laptop, handheld computer, or cloud server. The data verification device 20 based on jigsaw puzzle rules may include, but is not limited to, a processor 21 and a memory 22. Those skilled in the art will understand that the schematic diagram is merely an example of the data verification device 20 based on jigsaw puzzle rules and does not constitute a limitation on the device. It may include more or fewer components than illustrated, or combine certain components, or use different components. For example, the data verification device 20 based on jigsaw puzzle rules may also include input / output devices, network access devices, buses, etc.

[0094] The processor 21 can be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor can be a microprocessor or any conventional processor. The processor 21 is the control center of the jigsaw puzzle-based data verification device 20, connecting all parts of the device through various interfaces and lines.

[0095] The memory 22 can be used to store the computer program and / or modules. The processor 21 implements various functions of the data verification device 20 based on the puzzle rule by running or executing the computer program and / or modules stored in the memory 22 and calling the data stored in the memory 22. The memory 22 may mainly include a program storage area and a data storage area. The program storage area may store the operating system, at least one application program required for a function (such as sound playback function, image playback function, etc.), etc.; the data storage area may store data created according to the use of the mobile phone (such as audio data, phonebook, etc.). In addition, the memory 22 may include high-speed random access memory, and may also include non-volatile memory, such as hard disk, memory, plug-in hard disk, smart media card (SMC), secure digital (SD) card, flash card, at least one disk storage device, flash memory device, or other volatile solid-state storage device.

[0096] The module integrated into the data verification device 20 based on puzzle rules, if implemented as a software functional unit and sold or used as an independent product, can be stored in a computer-readable storage medium. Based on this understanding, all or part of the processes in the above embodiments of the present invention can also be implemented by a computer program instructing related hardware. The computer program can be stored in a computer-readable storage medium, and when executed by the processor 21, it can implement the steps of the various method embodiments described above. The computer program includes computer program code, which can be in the form of source code, object code, executable files, or certain intermediate forms. The computer-readable medium can include: any entity or device capable of carrying the computer program code, recording media, USB flash drives, portable hard drives, magnetic disks, optical disks, computer memory, read-only memory (ROM), random access memory (RAM), electrical carrier signals, telecommunication signals, and software distribution media, etc. It should be noted that the content contained in the computer-readable medium may be appropriately added to or subtracted from the content as required by the legislation and patent practice in the jurisdiction. For example, in some jurisdictions, according to legislation and patent practice, the computer-readable medium may not include electrical carrier signals and telecommunication signals.

[0097] It should be noted that the device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs. Furthermore, in the accompanying drawings of the device embodiments provided by this invention, the connection relationships between modules indicate that they have communication connections, which can be specifically implemented as one or more communication buses or signal lines. Those skilled in the art can understand and implement this without any creative effort.

[0098] This invention also provides a computer-readable storage medium, which includes a stored computer program, wherein the computer program, when running, controls the device where the computer-readable storage medium is located to execute the data verification method based on jigsaw puzzle rules as described in the above embodiments.

[0099] Furthermore, embodiments of the present invention also provide a computer program product, which is stored in a storage medium and executed by at least one processor to implement the steps of the data verification method based on jigsaw puzzle rules described in the above embodiments.

[0100] The above description represents the preferred embodiments of the present invention. It should be noted that those skilled in the art can make various improvements and modifications without departing from the principles of the present invention, and these improvements and modifications are also considered to be within the scope of protection of the present invention.

Claims

1. A data verification method based on jigsaw puzzle rules, characterized in that, include: Acquire historical flight data for a certain period of time; wherein, the historical flight data includes at least flight segment data, flow direction data, and fuel volume data; The historical flight data is subjected to anomaly verification using preset mosaic rules to obtain abnormal flight data that conforms to the preset mosaic rules; wherein, the preset mosaic rules include at least segment mosaic rules, flow direction mosaic rules, and fuel quantity mosaic rules; If no abnormal flight data matches the preset jigsaw puzzle rules, the preset jigsaw puzzle rules are checked and updated.

2. The data verification method based on jigsaw puzzle rules as described in claim 1, characterized in that, The step of performing anomaly verification on the historical flight data using preset jigsaw puzzle rules to obtain anomaly flight data that conforms to the preset jigsaw puzzle rules includes: The preset jigsaw puzzle rules are parsed to generate the rule formulas for the preset jigsaw puzzle rules; Based on the table fields of the rule formula, the historical flight data is retrieved to obtain the historical flight data corresponding to the table fields. Substituting the values ​​of the corresponding historical flight data into the rule formula yields abnormal flight data that conforms to the preset jigsaw puzzle rules.

3. The data verification method based on jigsaw puzzle rules as described in claim 1, characterized in that, The method for generating the preset puzzle rules includes: The jigsaw puzzle rule tool is used to set the rule value range and rule conditions of the preset jigsaw puzzle rule, and the set rule value range and rule conditions are assembled to obtain the corresponding preset jigsaw puzzle rule.

4. The data verification method based on jigsaw puzzle rules as described in claim 3, characterized in that, The puzzle rule tool includes a baseline table, a reference table, tool blocks, variable blocks, a puzzle board, and a function area; The benchmark table and the comparison table are used to provide table fields that conform to the value range of the rules; The tool block is used to concatenate the table fields and add annotations to obtain the rule value puzzle of the table fields, and to perform combination operations on the rule value puzzle to obtain the rule condition puzzle of the rule value puzzle; The variable block is used to store the rule value puzzle; The puzzle board is used to assemble the rule value puzzle and the rule condition puzzle to obtain the corresponding preset puzzle rule; The function area is used to save the corresponding preset puzzle rules and view the description of the corresponding preset puzzle rules.

5. The data verification method based on jigsaw puzzle rules as described in claim 1, characterized in that, If no abnormal flight data matching the preset puzzle rule is found, the preset puzzle rule is checked and updated, including: If no abnormal segment data conforms to the segment mosaic rules, the segment mosaic rules are checked and updated. If no abnormal flow data conforms to the flow pattern rules, the flow pattern rules are checked and updated. If no abnormal oil volume data matching the oil volume mosaic rule is found, the oil volume mosaic rule is checked and updated.

6. The data verification method based on jigsaw puzzle rules as described in claim 1, characterized in that, The flight segment mosaic rules are used to check whether there are any anomalies in the flight segment data in the historical flight data; The flow direction puzzle rule is used to check whether there are any anomalies in the flow direction data in the historical flight data; The fuel quantity mosaic rule is used to check whether there are any anomalies in the fuel quantity data in the historical flight data.

7. A data verification device based on jigsaw puzzle rules, characterized in that, include: The flight data acquisition module is used to acquire historical flight data over a certain period of time; wherein, the historical flight data includes at least flight segment data, flow direction data, and fuel volume data; An abnormal data verification module is used to perform abnormal data verification on the historical flight data using preset puzzle rules to obtain abnormal flight data that conforms to the preset puzzle rules; wherein, the preset puzzle rules include at least flight segment puzzle rules, flow direction puzzle rules, and fuel quantity puzzle rules; The puzzle rule update module is used to check the preset puzzle rule and update it if there is no abnormal flight data that matches the preset puzzle rule.

8. A data verification device based on jigsaw puzzle rules, characterized in that, The system includes a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor, wherein the processor, when executing the computer program, implements the data verification method based on jigsaw puzzle rules as described in any one of claims 1-6.

9. A computer-readable storage medium, characterized in that, The computer-readable storage medium includes a stored computer program, wherein, when the computer program is executed, it controls the device where the computer-readable storage medium is located to perform the data verification method based on jigsaw puzzle rules as described in any one of claims 1-6.

10. A computer program product, characterized in that, The computer program product is stored in a storage medium, and the program product is executed by at least one processor to implement the steps of the data verification method based on jigsaw puzzle rules as described in any one of claims 1-6.

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